Instructions to use ProbeX/Model-J__SupViT__model_idx_0429 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__SupViT__model_idx_0429 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__SupViT__model_idx_0429") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0429") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0429") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fdeb6964dbca3eb22b86fb5cd1574fc1be691dd0de354f5514d2232779d94faa
- Size of remote file:
- 5.37 kB
- SHA256:
- 69205b0e35d53587574c26926e0ff34066d699d2622d2164351696775b0b8918
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